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  • SAGE Publications  (5)
  • Yang, Jun  (5)
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  • SAGE Publications  (5)
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  • 1
    Online Resource
    Online Resource
    Experimental and simulation study on the thermal characteristics of the high-speed spindle system
    SAGE Publications ; 2017
    In:  Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science Vol. 231, No. 6 ( 2017-03), p. 1072-1093
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, SAGE Publications, Vol. 231, No. 6 ( 2017-03), p. 1072-1093
    Abstract: High-speed spindles often suffer from degeneration in its machining accuracy caused by the uneven distribution of temperature field. In order to improve the machining accuracy of high-speed spindles, a three-dimensional (3D) finite element analysis (FEA) model, which considered the combined effect of thermal contact resistance (TCR) and the change in heat power and stiffness caused by thermal displacements of bearing components on the accuracy of simulation results, was proposed to conduct transient thermal-structure analysis of high-speed spindles. The predictive model for TCR was proposed based on the fractal theory to characterize the rough surface morphology with disorder, self-affinity and non-stationary random features. And a contact mechanics model was developed to consider the influence of asperities’ deformation on TCR. The thermal-structure model of bearing was proposed to calculate the heat power and stiffness based on the quasi-static mechanics analysis. The FEA model proposed in this paper was used to simulate the temperature field distribution and thermal deformations of the high-speed spindle system. Then thermal characteristic experiments were conducted to validate the effectiveness of this model. The results showed that the FEA model was much more accurate than the traditional model which ignored the above two important factors. The temperature field and thermal errors of the spindle system were analyzed.
    Type of Medium: Online Resource
    ISSN: 0954-4062 , 2041-2983
    URL: Article
    DOI: 10.1177/0954406216631573
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
    detail.hit.zdb_id: 2024890-8
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Thermal error compensation on a computer numerical control machine tool considering thermal tilt angles and cutting tool length
    SAGE Publications ; 2015
    In:  Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Vol. 229, No. 1_suppl ( 2015-02), p. 78-97
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, SAGE Publications, Vol. 229, No. 1_suppl ( 2015-02), p. 78-97
    Abstract: The present error compensation technology of computer numerical control machine tools ignores radial thermal tilt angle errors of the spindle, while the thermal-induced offset is closely related to the tilt angle and the handle length. To solve this problem, three models of spindle thermal errors are proposed for the thermal yaw, pitch angles and elongation, and error compensation is performed based on the thermal tilt angles and cutting tool length. A five-point method was applied to measure the spindle thermal drifts at different speeds by eddy current sensors, which could effectively analyse the changes in the position-pose of the errors. Fuzzy clustering and correlation analysis were applied to group and optimise the temperature variables and select the variables sensitive to thermal errors in order to depress the multicollinearity of the temperature variables and improve the stability of the model. Finally, the thermal offset compensation was conducted in three directions. The results indicate that back propagation has a better capability for nonlinear fitting, but its generalisation is far less than that of time series. While the structure of multiple linear regression analysis is simple, its prediction accuracy is not satisfied. Time series adequately reflects the dynamic behaviours of the thermal error, and the prediction accuracy can reach 94%, with excellent robustness under different cutting conditions. The thermal error compensation equation that includes thermal tilt angles and cutting tool length is suitable for actual conditions and can accurately describe the space-pose of the thermal deformation and improve the machining accuracy.
    Type of Medium: Online Resource
    ISSN: 0954-4054 , 2041-2975
    URL: Article
    DOI: 10.1177/0954405414556499
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2032745-6
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Thermal error simulation and compensation in a jig-boring machine equipped with a dual-drive servo feed system
    SAGE Publications ; 2015
    In:  Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Vol. 229, No. 1_suppl ( 2015-02), p. 43-63
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, SAGE Publications, Vol. 229, No. 1_suppl ( 2015-02), p. 43-63
    Abstract: A jig-boring machine equipped with a dual-drive servo system can operate with high speed and accuracy. However, different friction behaviours and asymmetrical preloads of the double drive structures as well as asynchronous control over the master-slave motors can make the machine produce tremendous heat, causing uneven temperature distributions in the feed system and eventually leading to thermal deformation that reduces the positional accuracy of machines. To investigate the effects of thermal behaviours on machining accuracy, the thermal–structure finite element method was employed to analyse the transient thermal deformation and temperature field of the machine at different feed rates, considering boundary conditions such as the convective heat transfer coefficient and heat generation by motors, bearings, and screws. Additionally, a synchronous acquisition system was developed to measure the thermal behaviours, and the transient changes in temperature and deformation were compared with simulated values. Consequently, a synthetic thermal model was established to make accurate predictions based on the analysis of relationships between thermal error and equilibrium time, coordinate position and screw temperature. Finally, thermal error compensation was performed using a feedback integration method. The experimental data indicate that the finite element method model can accurately predict temperature distributions and thermal errors. Moreover, thermal errors were compensated at 24.1 °C and 22.6 °C with a feed rate of 18 m/min, and machining accuracy was increased by 73% and 62%, respectively.
    Type of Medium: Online Resource
    ISSN: 0954-4054 , 2041-2975
    URL: Article
    DOI: 10.1177/0954405414555592
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2032745-6
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    Online Resource
  • 4
    Online Resource
    Online Resource
    A geometrical–mechanical–thermal predictive model for thermal contact conductance in vacuum environment
    SAGE Publications ; 2016
    In:  Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Vol. 230, No. 8 ( 2016-08), p. 1451-1464
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, SAGE Publications, Vol. 230, No. 8 ( 2016-08), p. 1451-1464
    Abstract: In this article, a comprehensive geometrical–mechanical–thermal predictive model is developed for thermal contact conductance between two flat metallic rough surfaces. The rough surface was characterized by Weierstrass–Mandelbrot fractal function. The micro-morphology was measured by laser microscope to identify the fractal parameters that were then applied to mechanical and thermal modeling. A new contact mechanics model was then proposed to calculate the contact parameters, and different contact scales between asperities and three modes of deformation, elastic, elastic–plastic and fully plastic, were taken into account. The normal contact pressure, which should be equal to the exterior load, was formulated as a function of the fractal parameters, the maximum contact area and the material physical properties of the given surface. Based on the contact mechanics model, first a single pair of contacting asperities was proposed and then multi-contacting asperities were combined to get total thermal contact conductance. The influences of contact load, surface roughness, asperity top radius and contact area as well as the temperature on the thermal contact conductance were investigated by using the proposed model. The investigation results showed that thermal contact conductance increases with the contact load and contact area. The larger the surface roughness, the smaller is the thermal contact conductance. Finally, the experiments were conducted to validate the effectiveness of the thermal contact conductance modeling. This geometrical–mechanical–thermal predictive model was compared with the two existing predictive models and a series of experimental data. The results showed good agreement, demonstrating the validity of the model and providing certainty for further study on the heat transfer between contact surfaces.
    Type of Medium: Online Resource
    ISSN: 0954-4054 , 2041-2975
    URL: Article
    DOI: 10.1177/0954405415611358
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
    detail.hit.zdb_id: 2032745-6
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  • 5
    Online Resource
    Online Resource
    Thermal error compensation based on genetic algorithm and artificial neural network of the shaft in the high-speed spindle system
    SAGE Publications ; 2017
    In:  Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Vol. 231, No. 5 ( 2017-04), p. 753-767
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, SAGE Publications, Vol. 231, No. 5 ( 2017-04), p. 753-767
    Abstract: To improve the accuracy, generality and convergence of thermal error compensation model based on traditional neural networks, a genetic algorithm was proposed to optimize the number of the nodes in the hidden layer, the weights and the thresholds of the traditional neural network by considering the shortcomings of the traditional neural networks which converged slowly and was easy to fall into local minima. Subsequently, the grey cluster grouping and statistical correlation analysis were proposed to group temperature variables and select thermal sensitive points. Then, the thermal error models of the high-speed spindle system were proposed based on the back propagation and genetic algorithm–back propagation neural networks with practical thermal error sample data. Moreover, thermal error compensation equations of three directions and compensation strategy were presented, considering thermal elongation and radial tilt angles. Finally, the real-time thermal error compensation was implemented on the jig borer’s high-speed spindle system. The results showed that genetic algorithm–back propagation models showed its effectiveness in quickly solving the global minimum searching problem with perfect convergence and robustness under different working conditions. In addition, the spindle thermal error compensation method based on the genetic algorithm–back propagation neural network can improve the jig borer’s machining accuracy effectively. The results of thermal error compensation showed that the axial accuracy was improved by 85% after error compensation, and the axial maximum error decreased from 39 to 3.6 µm. Moreover, the X/ Y-direction accuracy can reach up to 82% and 85%, respectively, which demonstrated the effectiveness of the proposed methodology of measuring, modeling and compensating.
    Type of Medium: Online Resource
    ISSN: 0954-4054 , 2041-2975
    URL: Article
    DOI: 10.1177/0954405416639893
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
    detail.hit.zdb_id: 2032745-6
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    Online Resource
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